Overview
In recent years, Reactive programming has gained popularity. Now it is frequently utilized programming paradigm in the creation of cutting-edge, responsive, and scalable systems. Based on the concepts of asynchronous data streams, reactive programming offers a method for handling events and data flows non-blocking and responsively. In this blog post, we will provide an introduction to Reactive Programming and explore its key concepts and benefits.
What is Reactive Programming?
A programming paradigm called reactive programming emphasizes the reactive transmission of data changes and events. Data is seen as a stream of events in reactive programming, and programmers create code that responds to changes in the data stream as they happen. Observables, which are objects that emit a stream of data over time, are the foundation of the notion of reactive programming.
Reactive programming’s key benefit is that it offers a technique to handle complex and dynamic data flows in a responsive and scalable way. Applications that require real-time data processing, such as web apps, IoT devices, and streaming services, are particularly well suited for reactive programming. Reactive programming’s key benefit is that it offers a technique to handle complex and dynamic data flows in a responsive and scalable way. Applications that require real-time data processing, such as web apps, IoT devices, and streaming services, are particularly well suited for reactive programming.
Key Concepts of Reactive Programming
There are several key concepts that are central to Reactive Programming:
- Observables: Observables are things that continuously emit a stream of data. Any number of events, such as error and completion events, can be produced by an observable.
- Observers: Observers are objects that subscribe to an Observable and get alerts whenever new data is emitted from the Observable. Errors and completion events can also be handled by observers.
- Operators: Observables emit data, which is transformed, filtered, or combined by operators. Operators are used to manipulate the data released by Observables and to build more intricate data flows.
- Schedulers: In reactive programming, schedulers are used to manage the parallelism and timeliness of data streams. Schedulers can be used to enhance performance and resource usage since they let developers control how and when data streams are processed.
Benefits of Reactive Programming
Reactive Programming offers several benefits over traditional programming paradigms:
- Responsiveness: Applications can react rapidly and effectively to changes in data streams thanks to reactive programming. This is especially crucial for real-time data processing applications like web applications, IoT devices, and streaming services.
- Scalability: A scalable and effective method of managing intricate and dynamic data flows is provided by reactive programming. Applications that can manage enormous volumes of data and scale effectively as the data grows can be created using reactive programming.
- Resilience: A reactive and non-blocking method of addressing mistakes and failures is provided by reactive programming. Applications can be created using reactive programming that is resilient to mistakes and has a short recovery time after failures.
- Modularity: Application builders can create modular and composable systems using reactive programming. By encapsulating data flows and logic in reusable and assemblable components, reactive programming enables the creation of more intricate programs.
Data flow as a driven system
If we talk about this diagram this is a typical and traditional approach. Basically, the client sends a request to the application then the request goes to the database and processes the data. Finally, it returns a response back to the client. But what if a few records are inserted or modified in the middle. As a result, the client will have no information about those records. To get that updated information again we need to do a separate restAPI call. Now let us talk about how it works on reactive programming. Now whoever subscribes, can stream the data. If there are any changes done in the database then immediately it will fire or publish an event “there is a new data found”.
In this case, if you observe the client is a subscriber and the database driver is a publisher. If any changes will happen to the database will publish an event. As my client is consuming the application, he can easily stream the data. And also in this scenario, the connection will always be in an open state. That is the reason why we can perform the publisher and subscriber operation.
We can consider any steaming platform that works in a reactive programming manner. Therefore, the best example we can consider is cricket live score. We have seen the cricket live score right. If any update happened in the application, we can see the current score with the updated details. So this is how data is transferred as an event on the publisher and subscriber model.
Conclusion
In conclusion, in this blog, we have learned about the basics of Reactive Programming. I will be covering more topics on Reactive Programming in my future blogs, stay connected. Happy learning 🙂
For more, you can refer to the Liquibase documentation: https://projectreactor.io/docs/core/release/reference/#intro-reactive
For a more technical blog, you can refer to the Knoldus blog: https://blog.knoldus.com/
